Waste 7-1 7. Waste 1 Waste management and treatment activities are sources of greenhouse gas emissions (see Figure 7-1). Landfills 2 accounted for approximately 16.2 percent of total U.S. anthropogenic methane (CH4) emissions in 2017, the third 3 largest contribution of any CH4 source in the United States. Additionally, wastewater treatment and composting of 4 organic waste accounted for approximately 2.2 percent and 0.3 percent of U.S. CH4 emissions, respectively. Nitrous 5 oxide (N2O) emissions from the discharge of wastewater treatment effluents into aquatic environments were 6 estimated, as were N2O emissions from the treatment process itself. Nitrous oxide emissions from composting were 7 also estimated. Together, these waste activities account for 1.9 percent of total U.S. N2O emissions. Nitrogen oxides 8 (NOx), carbon monoxide (CO), and non-CH4 volatile organic compounds (NMVOCs) are emitted by waste 9 activities, and are addressed separately at the end of this chapter. A summary of greenhouse gas emissions from the 10 Waste chapter is presented in Table 7-1 and Table 7-2. 11 Figure 7-1: 2017 Waste Chapter Greenhouse Gas Sources (MMT CO2 Eq.) 12 13 Overall, in 2017, waste activities generated emissions of 131.0 MMT CO2 Eq., or 2.0 percent of total U.S. 14 greenhouse gas emissions. 1 15 Table 7-1: Emissions from Waste (MMT CO2 Eq.) 16 Gas/Source 1990 2005 2013 2014 2015 2016 2017 CH4 195.2 148.7 129.3 129.0 127.9 124.4 124.2 Landfills 179.6 131.4 112.9 112.5 111.2 108.0 107.7 1 Emissions reported in the Waste chapter for landfills and wastewater treatment include those from all 50 states, including Hawaii and Alaska, as well as from U.S. Territories to the extent those waste management activities are occurring. Emissions for composting include all 50 states, including Hawaii and Alaska, but not U.S. Territories. Composting emissions from U.S. Territories are assumed to be small.
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Waste 7-1
7. Waste 1
Waste management and treatment activities are sources of greenhouse gas emissions (see Figure 7-1). Landfills 2
accounted for approximately 16.2 percent of total U.S. anthropogenic methane (CH4) emissions in 2017, the third 3
largest contribution of any CH4 source in the United States. Additionally, wastewater treatment and composting of 4
organic waste accounted for approximately 2.2 percent and 0.3 percent of U.S. CH4 emissions, respectively. Nitrous 5
oxide (N2O) emissions from the discharge of wastewater treatment effluents into aquatic environments were 6
estimated, as were N2O emissions from the treatment process itself. Nitrous oxide emissions from composting were 7
also estimated. Together, these waste activities account for 1.9 percent of total U.S. N2O emissions. Nitrogen oxides 8
(NOx), carbon monoxide (CO), and non-CH4 volatile organic compounds (NMVOCs) are emitted by waste 9
activities, and are addressed separately at the end of this chapter. A summary of greenhouse gas emissions from the 10
Waste chapter is presented in Table 7-1 and Table 7-2. 11
Figure 7-1: 2017 Waste Chapter Greenhouse Gas Sources (MMT CO2 Eq.) 12
13
Overall, in 2017, waste activities generated emissions of 131.0 MMT CO2 Eq., or 2.0 percent of total U.S. 14
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values. For years 1990 to 2004,
the Inventory methodology uses the first order decay methodology. A methodological change occurs in year 2005. For
years 2005 to 2017, directly reported net CH4 emissions from the GHGRP data plus a scale-up factor are used to
account for emissions from landfill facilities that are not subject to the GHGRP. These data incorporate CH4 recovered
and oxidized. As such, CH4 generation and CH4 recovery are not calculated separately. See the Time-Series
Consistency section of this chapter for more information.
Methodology 7
Methodology Applied for MSW Landfills 8
Methane emissions from landfills can be estimated using two primary methods. The first method uses the first order 9
decay (FOD) model as described by the 2006 IPCC Guidelines to estimate CH4 generation. The amount of CH4 10
recovered and combusted from MSW landfills is subtracted from the CH4 generation and is then adjusted with an 11
oxidation factor. The oxidation factor represents the amount of CH4 in a landfill that is oxidized to CO2 as it passes 12
through the landfill cover (e.g., soil, clay, geomembrane). This method is presented below and is similar to Equation 13
HH-5 in 40 CFR Part 98.343 for MSW landfills, and Equation TT-6 in 40 CFR Part 98.463 for industrial waste 14
landfills. 15
CH4,Solid Waste = [CH4,MSW + CH4,Ind − R] − Ox
where,
16
17
7-6 DRAFT Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2017
CH4,Solid Waste = Net CH4 emissions from solid waste
CH4,MSW = CH4 generation from MSW landfills
CH4,Ind = CH4 generation from industrial waste landfills
R = CH4 recovered and combusted (only for MSW landfills)
Ox = CH4 oxidized from MSW and industrial waste landfills before release to the atmosphere
1
2
3
4
5
The second method used to calculate CH4 emissions from landfills, also called the back-calculation method, is based 6
on directly measured amounts of recovered CH4 from the landfill gas and is expressed below and by Equation HH-8 7
in 40 CFR Part 98.343. The two parts of the equation consider the portion of CH4 in the landfill gas that is not 8
collected by the landfill gas collection system, and the portion that is collected. First, the recovered CH4 is adjusted 9
with the collection efficiency of the gas collection and control system and the fraction of hours the recovery system 10
operated in the calendar year. This quantity represents the amount of CH4 in the landfill gas that is not captured by 11
the collection system; this amount is then adjusted for oxidation. The second portion of the equation adjusts the 12
portion of CH4 in the collected landfill gas with the efficiency of the destruction device(s), and the fraction of hours 13
the destruction device(s) operated during the year. 14
CH4,Solid Waste = [(𝑅
𝐶𝐸 𝑥 𝑓𝑅𝐸𝐶− 𝑅) 𝑥(1 − 𝑂𝑋) + 𝑅 𝑥 (1 − (𝐷𝐸 𝑥 𝑓𝐷𝑒𝑠𝑡))]
where,
CH4,Solid Waste = Net CH4 emissions from solid waste
R = Quantity of recovered CH4 from Equation HH-4 of EPA’s GHGRP
CE = Collection efficiency estimated at the landfill, considering system coverage, operation,
and cover system materials from Table HH-3 of EPA’s GHGRP. If area by soil cover type
information is not available, the default value of 0.75 should be used. (percent)
fREC = fraction of hours the recovery system was operating (percent)
OX = oxidation factor (percent)
DE = destruction efficiency (percent)
fDest = fraction of hours the destruction device was operating (fraction)
15
16
17
18
19
20
21
22
23
24
25
26
27
The current Inventory uses both methods to estimate CH4 emissions across the time series. Prior to the 1990 through 28
2015 Inventory, only the FOD method was used. Methodological changes were made to the 1990 through 2015 29
Inventory to incorporate higher tier data (i.e., directly reported CH4 emissions to EPA’s GHGRP), which cannot be 30
directly applied to earlier years in the time series without significant bias. The technique used to merge the directly 31
reported GHGRP data with the previous methodology is described as the overlap technique in the Time-Series 32
Consistency chapter of the 2006 IPCC Guidelines. Additional details on the technique used is included in the Time 33
Series Consistency section of this chapter and a technical memorandum (RTI 2017). 34
A summary of the methodology used to generate the current 1990 through 2017 Inventory estimates for MSW 35
landfills is as follows and also illustrated in Annex Figure A-18: 36
• 1940 through 1989: These years are included for historical waste disposal amounts. Estimates of the 37
annual quantity of waste landfilled for 1960 through 1988 were obtained from EPA’s Anthropogenic 38
Methane Emissions in the United States, Estimates for 1990: Report to Congress (EPA 1993) and an 39
extensive landfill survey by the EPA’s Office of Solid Waste in 1986 (EPA 1988). Although waste placed 40
in landfills in the 1940s and 1950s contributes very little to current CH4 generation, estimates for those 41
years were included in the FOD model for completeness in accounting for CH4 generation rates and are 42
based on the population in those years and the per capita rate for land disposal for the 1960s. For the 43
Inventory calculations, wastes landfilled prior to 1980 were broken into two groups: wastes disposed in 44
managed, anaerobic landfills (Methane Conversion Factor, MCF, of 1) and those disposed in uncategorized 45
solid waste disposal waste sites (MCF of 0.6) (IPCC 2006). Uncategorized sites represent those sites for 46
which limited information is known about the management practices. All calculations after 1980 assume 47
waste is disposed in managed, anaerobic landfills. The FOD method was applied to estimate annual CH4 48
generation. Methane recovery amounts were then subtracted and the result was then adjusted with a 10 49
percent oxidation factor to derive the net emissions estimates. 50
Waste 7-7
• 1990 through 2004: The Inventory time series begins in 1990. The FOD method is exclusively used for 1
this group of years. The national total of waste generated (based on state-specific landfill waste generation 2
data) and a national average disposal factor for 1989 through 2004 were obtained from the State of Garbage 3
(SOG) survey every two years (i.e., 2002, 2004 as published in BioCycle 2006). In-between years were 4
interpolated based on population growth. For years 1989 to 2000, directly reported total MSW generation 5
data were used; for other years, the estimated MSW generation (excluding construction and demolition 6
waste and inerts) were presented in the reports and used in the Inventory. The FOD method was applied to 7
estimate annual CH4 generation. Landfill-specific CH4 recovery amounts were then subtracted from CH4 8
generation and the result was then adjusted with a 10 percent oxidation factor to derive the net emissions 9
estimates. 10
• 2005 through 2009: Emissions for these years are estimated using net CH4 emissions that are reported by 11
landfill facilities under EPA’s GHGRP. Because not all landfills in the United States are required to report 12
to EPA’s GHGRP, a 9 percent scale-up factor is applied to the GHGRP emissions for completeness. 13
Supporting information, including details on the technique used to estimate emissions for 2005 to 2009 and 14
to ensure time-series consistency by incorporating the directly reported GHGRP emissions is presented in 15
Annex 3.14 and in RTI 2018a. A single oxidation factor is not applied to the annual CH4 generated as is 16
done for 1990 to 2004 because the GHGRP emissions data are used, which already take oxidation into 17
account. The GHGRP allows facilities to use varying oxidation factors depending on their facility-specific 18
calculated CH4 flux rate (i.e., 0, 10, 25, or 35 percent). The average oxidation factor from the GHGRP 19
facilities is 19.5 percent. 20
• 2010 through 2017: Directly reported net CH4 emissions to the GHGRP are used with a 9 percent scale-up 21
factor to account for landfills that are not required to report to the GHGRP. A combination of the FOD 22
method and the back-calculated CH4 emissions were used by the facilities reporting to the GHGRP. 23
Landfills reporting to the GHGRP without gas collection and control apply the FOD method, while most 24
landfills with landfill gas collection and control apply the back-calculation method. As noted above, 25
GHGRP facilities use a variety of oxidation factors. The average oxidation factor from the GHGRP 26
facilities is 19.5 percent. 27
A detailed discussion of the data sources and methodology used to calculate CH4 generation and recovery is 28
provided below. Supporting information, including details on the technique used to ensure time-series consistency 29
by incorporating the directly reported GHGRP emissions is presented in the Time-Series Consistency section of this 30
chapter and in Annex 3.14. 31
Description of the Methodology for MSW Landfills as Applied for 1990-2004 32
National MSW Methane Generation and Disposal Estimates 33
States and local municipalities across the United States do not consistently track and report quantities of MSW 34
generated or collected for management, nor do they report end-of-life disposal methods to a centralized system. 35
Therefore, national MSW landfill waste generation and disposal data are obtained from secondary data, specifically 36
the SOG surveys, published approximately every two years, with the most recent publication date of 2014. The SOG 37
survey was the only continually updated nationwide survey of waste disposed in landfills in the United States and 38
was the primary data source with which to estimate nationwide CH4 generation from MSW landfills. Currently, 39
EPA’s GHGRP waste disposal data and MSW management data published by EREF are available. 40
The SOG surveys collect data from the state agencies and then apply the principles of mass balance where all MSW 41
generated is equal to the amount of MSW landfilled, combusted in waste-to-energy plants, composted, and/or 42
recycled (BioCycle 2006; Shin 2014). This approach assumes that all waste management methods are tracked and 43
reported to state agencies. Survey respondents are asked to provide a breakdown of MSW generated and managed 44
by landfilling, recycling, composting, and combustion (in waste-to-energy facilities) in actual tonnages as opposed 45
to reporting a percent generated under each waste disposal option. The data reported through the survey have 46
typically been adjusted to exclude non-MSW materials (e.g., industrial and agricultural wastes, construction and 47
demolition debris, automobile scrap, and sludge from wastewater treatment plants) that may be included in survey 48
responses. While these wastes may be disposed of in MSW landfills, they are not the primary type of waste material 49
7-8 DRAFT Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2017
disposed and are typically inert. In the most recent survey, state agencies were asked to provide already filtered, 1
MSW-only data. Where this was not possible, they were asked to provide comments to better understand the data 2
being reported. All state disposal data are adjusted for imports and exports across state lines where imported waste is 3
included in a state’s total while exported waste is not. Methodological changes have occurred over the time frame 4
the SOG survey has been published, and this has affected the fluctuating trends observed in the data (RTI 2013). 5
State-specific landfill MSW generation data and a national average disposal factor for 1989 through 2004 were 6
obtained from the SOG survey every two years (i.e., 2002, 2004 as published in BioCycle 2006). The landfill 7
inventory calculations start with hard numbers (where available) as presented in the SOG documentation for the 8
report years 2002 and 2004. In-between year waste generation is interpolated using the prior and next SOG report 9
data. For example, waste generated in 2003 = (waste generation in 2002 + waste generation in 2004)/2. The 10
quantities of waste generated across all states are summed and that value is then used as the nationwide quantity of 11
waste generated in each year of the time series. The SOG survey is voluntary and not all states provide data in each 12
survey year. To estimate waste generation for states that did not provide data in any given reporting year, one of the 13
following methods was used (RTI 2013): 14
• For years when a state-specific waste generation rate was available from the previous SOG reporting year 15
submission, the state-specific waste generation rate for that particular state was used. 16
– or – 17
• For years where a state-specific waste generation rate was not available from the previous SOG reporting 18
year submission, the waste amount is generated using the national average waste generation rate. In other 19
words, Waste Generated = Reporting Year Population × the National Average Waste Generation Rate 20
o The National Average Waste Generation Rate is determined by dividing the total reported waste 21
generated across the reporting states by the total population for reporting states. 22
o This waste generation rate may be above or below the waste generation rate for the non-reporting 23
states and contributes to the overall uncertainty of the annual total waste generation amounts used 24
in the model. 25
Use of these methods to estimate solid waste generated by states is a key aspect of how the SOG data was 26
manipulated and why the results differ for total solid waste generated as estimated by SOG and in the Inventory. In 27
the early years (2002 data in particular), SOG made no attempt to fill gaps for non-survey responses. For the 2004 28
data, the SOG team used proxy data (mainly from the WBJ) to fill gaps for non-reporting states and survey 29
responses. 30
Another key aspect of the SOG survey is that it focuses on MSW-only data. The data states collect for solid waste 31
typically are representative of total solid waste and not the MSW-only fraction. In the early years of the SOG 32
survey, most states reported total solid waste rather than MSW-only waste. The SOG team, in response, “filtered” 33
the state-reported data to reflect the MSW-only portion. 34
This data source also contains the waste generation data reported by states to the SOG survey, which fluctuates from 35
year to year. Although some fluctuation is expected, for some states, the year-to-year fluctuations are quite 36
significant (>20 percent increase or decrease in some case) (RTI 2013). The SOG survey reports for these years do 37
not provide additional explanation for these fluctuations and the source data are not available for further assessment. 38
Although exact reasons for the large fluctuations are difficult to obtain without direct communication with states, 39
staff from the SOG team that were contacted speculate that significant fluctuations are present because the particular 40
state could not gather complete information for waste generation (i.e., they are missing part of recycled and 41
composted waste data) during a given reporting year. In addition, SOG team staff speculated that some states may 42
have included C&D and industrial wastes in their previous MSW generation submissions, but made efforts to 43
exclude that (and other non-MSW categories) in more recent reports (RTI 2013). 44
Recently, the EREF published a report, MSW Management in the United States, which includes state-specific 45
landfill MSW generation and disposal data for 2010 and 2013 using a similar methodology as the SOG surveys 46
(EREF 2016). Because of this similar methodology, EREF data were used to populate data for years where BioCycle 47
data was not available when possible. State-specific landfill waste generation data for the years in between the SOG 48
surveys and EREF report (e.g., 2001, 2003, etc.) were either interpolated or extrapolated based on the SOG or EREF 49
data and the U.S. Census population data (U.S. Census Bureau 2018). 50
Waste 7-9
Estimates of the quantity of waste landfilled from 1989 to 2004 are determined by applying an average national 1
waste disposal factor to the total amount of waste generated (i.e., the SOG data). A national average waste disposal 2
factor is determined for each year an SOG survey is published and equals the ratio of the total amount of waste 3
landfilled in the United States to the total amount of waste generated in the United States. The waste disposal factor 4
is interpolated or extrapolated for the years in-between the SOG surveys, as is done for the amount of waste 5
generated for a given survey year. 6
The 2006 IPCC Guidelines recommend at least 50 years of waste disposal data to estimate CH4 emissions. Estimates 7
of the annual quantity of waste landfilled for 1960 through 1988 were obtained from EPA’s Anthropogenic Methane 8
Emissions in the United States, Estimates for 1990: Report to Congress (EPA 1993) and an extensive landfill survey 9
by the EPA’s Office of Solid Waste in 1986 (EPA 1988). Although waste placed in landfills in the 1940s and 1950s 10
contributes very little to current CH4 generation, estimates for those years were included in the FOD model for 11
completeness in accounting for CH4 generation rates and are based on the population in those years and the per 12
capita rate for land disposal for the 1960s. For calculations in the current Inventory, wastes landfilled prior to 1980 13
were broken into two groups: wastes disposed in landfills (MCF of 1) and those disposed in uncategorized site as 14
(MCF of 0.6). All calculations after 1980 assume waste is disposed in managed, modern landfills. See Annex 3.14 15
for more details. 16
In the current Inventory methodology, the MSW generation and disposal data are no longer used to estimate CH4 17
emissions for the years 2005 to 2017 because EPA’s GHGRP emissions data are now used for those years. 18
National Landfill Gas Recovery Estimates for MSW Landfills 19
The estimated landfill gas recovered per year (R) at MSW landfills for 1990 to 2004 was based on a combination of 20
four databases and includes recovery from flares and/or landfill gas-to-energy (LFGE) projects: 21
• EPA’s GHGRP dataset for MSW landfills (EPA 2015a);3 22
• A database developed by the Energy Information Administration (EIA) for the voluntary reporting of 23
greenhouse gases (EIA 2007); 24
• A database of LFGE projects that is primarily based on information compiled by the EPA LMOP (EPA 25
2016b);4 and 26
• The flare vendor database (contains updated sales data collected from vendors of flaring equipment). 27
The same landfill may be included one or more times across these four databases. To avoid double- or triple-28
counting CH4 recovery, the landfills across each database were compared and duplicates identified. A hierarchy of 29
recovery data is used based on the certainty of the data in each database. In summary, the GHGRP > EIA > LFGE > 30
flare vendor database. The rationale for this hierarchy is described below. 31
EPA’s GHGRP MSW landfills database was first introduced as a data source for landfill gas recovery in the 1990 to 32
2013 Inventory. EPA’s GHGRP MSW landfills database contains facility-reported data that undergoes rigorous 33
verification, thus it is considered to contain the least uncertain data of the four CH4 recovery databases. However, as 34
mentioned earlier, this database is unique in that it only contains a portion of the landfills in the United States 35
(although, presumably the highest emitters since only those landfills that meet a certain CH4 generation threshold 36
must report) and only contains data for 2010 and later. In the current Inventory methodology, CH4 recovery for 1990 37
to 2004 for facilities reporting to EPA’s GHGRP has been estimated using the directly reported emissions for those 38
facilities from 2010 to 2015, and an Excel forecasting function so that the GHGRP data source can be applied to 39
earlier years in the time series. Prior to 2005, if a landfill in EPA’s GHGRP was also in the LFGE or EIA databases, 40
the landfill gas project information, specifically the project start year, from either the LFGE or EIA databases was 41
used as the cutoff year for the estimated CH4 recovery in the GHGRP database. For example, if a landfill reporting 42
under EPA’s GHGRP was also included in the LFGE database under a project that started in 2002 that is still 43
3 The 2015 GHGRP dataset is used to estimate landfill gas recovery from MSW landfills for the years 1990 to 2004 of the
Inventory. This database is no longer updated because the methodology has changed such that the directly reported net methane
emissions from the GHGRP are used and landfill gas recovery is not separately estimated. 4 The LFGE database was not updated for the 1990 to 2017 Inventory because the methodology does not use this database for
years 2005 and later, thus the LMOP 2016 database is the most recent year reflected in the LFGE database for the Inventory.
7-10 DRAFT Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2017
operational, the CH4 recovery data in the GHGRP database for that facility was back-calculated to the year 2002 1
only. 2
If a landfill in the GHGRP MSW landfills database was also in the EIA, LFGE, and/or flare vendor database, the 3
avoided emissions were only based on EPA’s GHGRP MSW landfills database to avoid double or triple counting 4
the recovery amounts. In other words, the CH4 recovery from the same landfill was not included in the total recovery 5
from the EIA, LFGE, or flare vendor databases. 6
If a landfill in the EIA database was also in the LFGE and/or the flare vendor database, the CH4 recovery was based 7
on the EIA data because landfill owners or operators directly reported the amount of CH4 recovered using gas flow 8
concentration and measurements, and because the reporting accounted for changes over time. 9
If both the flare data and LFGE recovery data were available for any of the remaining landfills (i.e., not in the EIA 10
or GHGRP databases), then the avoided emissions were based on the LFGE data, which provides reported landfill-11
specific data on gas flow for direct use projects and project capacity (i.e., megawatts) for electricity projects. The 12
LFGE database is based on the most recent EPA LMOP database (published annually). The remaining portion of 13
avoided emissions is calculated by the flare vendor database, which estimates CH4 combusted by flares using the 14
midpoint of a flare’s reported capacity. New flare vendor sales data have not been collected since 2015 because 15
these data are not used for estimates beyond 2005 in the time series. Given that each LFGE project is likely to also 16
have a flare, double counting reductions from flares and LFGE projects in the LFGE database was avoided by 17
subtracting emission reductions associated with LFGE projects for which a flare had not been identified from the 18
emission reductions associated with flares (referred to as the flare correction factor). A further explanation of the 19
methodology used to estimate the landfill gas recovered can be found in Annex 3.14. 20
A destruction efficiency of 99 percent was applied to CH4 recovered to estimate CH4 emissions avoided due to the 21
combusting of CH4 in destruction devices (i.e., flares) in the EIA, LFGE, and flare vendor databases. The median 22
value of the reported destruction efficiencies to the GHGRP was 99 percent for all reporting years (2010 through 23
2017). For the other three recovery databases, the 99 percent destruction efficiency value selected was based on the 24
range of efficiencies (86 to greater than 99 percent) recommended for flares in EPA’s AP-42 Compilation of Air 25
Pollutant Emission Factors, Draft Section 2.4, Table 2.4-3 (EPA 2008). A typical value of 97.7 percent was 26
presented for the non-CH4 components (i.e., VOC and NMOC) in test results (EPA 2008). An arithmetic average of 27
98.3 percent and a median value of 99 percent are derived from the test results presented in EPA (2008). Thus, a 28
value of 99 percent for the destruction efficiency of flares has been used in the Inventory methodology. Other data 29
sources supporting a 99 percent destruction efficiency include those used to establish New Source Performance 30
Standards (NSPS) for landfills and in recommendations for shutdown flares used by the EPA LMOP. 31
National MSW Landfill Methane Oxidation Estimates 32
The amount of CH4 oxidized by the landfill cover at MSW landfills was assumed to be 10 percent of the CH4 33
generated that is not recovered (IPCC 2006; Mancinelli and McKay 1985; Czepiel et al. 1996) for the years 1990 to 34
2004. 35
National MSW Net Emissions Estimates 36
Net CH4 emissions are calculated by subtracting the CH4 recovered and CH4 oxidized from CH4 generated at MSW 37
landfills. 38
Description of the Methodology for MSW Landfills as Applied for 2005 to 2009 39
The Inventory methodology uses directly reported net CH4 emissions for the 2010 to 2017 reporting years from 40
EPA’s GHGRP to back-cast emissions for 2005 to 2009. The emissions for 2005 to 2009 are recalculated each year 41
the Inventory is published to account for the additional year of reported data and any revisions that facilities make to 42
past GHGRP reports. When EPA verifies the greenhouse gas reports, comparisons are made with data submitted in 43
earlier reporting years and errors may be identified in these earlier year reports. Facility representatives may submit 44
revised reports for any reporting year in order to correct these errors. Facilities reporting to EPA’s GHGRP that do 45
not have landfill gas collection and control systems use the FOD method. Facilities with landfill gas collection and 46
control must use both the FOD method and a back-calculation approach. The back-calculation approach starts with 47
Waste 7-11
the amount of CH4 recovered and works back through the system to account for gas not collected by the landfill gas 1
collection and control system (i.e., the collection efficiency). 2
A scale-up factor to account for emissions from landfills that do not report to EPA’s GHGRP is also applied 3
annually. In theory, national MSW landfill emissions should equal the net CH4 emissions reported to the GHGRP 4
plus net CH4 emissions from landfills that do not report to the GHGRP. EPA estimated a scale-up factor of 9 5
percent. The rationale behind the 9 percent scale-up factor is included in Annex 3.14 and in RTI 2018a. 6
The GHGRP data allows facilities to apply a range of oxidation factors (0.0, 0.10, 0.25, or 0.35) based on the 7
calculated CH4 flux at the landfill. Therefore, one oxidation factor is not applied for this time frame, as is done for 8
1990 to 2004. The average oxidation factor across the GHGRP data is 19.5 percent. 9
Description of the Methodology for MSW Landfills as Applied for 2010 to 2017 10
Directly reported CH4 emissions to the GHGRP are used for 2010 to 2017 plus the 9 percent scale-up factor to 11
account for emissions from landfills that do not report to the GHGRP. The average oxidation factor across the 12
GHGRP data is 19.5 percent. 13
Description of the First Order Decay Methodology for Industrial Waste Landfills 14
Emissions from industrial waste landfills are estimated from industrial production data (ERG 2018), waste disposal 15
factors, and the FOD method. There are currently no data sources that track and report the amount and type of waste 16
disposed of in the universe of industrial waste landfills in the United States. EPA’s GHGRP provides some insight 17
into waste disposal in industrial waste landfills, but is not comprehensive. Data reported to the GHGRP on industrial 18
waste landfills suggests that most of the organic waste which would result in methane emissions is disposed at pulp 19
and paper and food processing facilities. Of the 172 facilities that reported to subpart TT of the GHGRP in 2017, 93 20
(54 percent) are in the North American Industrial Classification System (NAICS) for Pulp, Paper, and Wood 21
Products (NAICS 321 and 322) and 12 (7 percent) are in Food Manufacturing (NAICS 311). Based on this limited 22
information, the Inventory methodology assumes most of the organic waste placed in industrial waste landfills 23
originates from the food processing (meat, vegetables, fruits) and pulp and paper sectors, thus estimates of industrial 24
landfill emissions focused on these two sectors. To validate this assumption, the EPA recently conducted an analysis 25
of data reported to subpart TT of the GHGRP in the 2016 reporting year. Waste streams of facilities reporting to 26
subpart TT were designated as either relating to food and beverage, pulp and paper, or other based on their primary 27
NAICS code. The total waste disposed by facilities under each primary NAICS reported in 2016 were calculated in 28
order to determine that 93 percent of the total organic waste quantity reported under subpart TT is originating from 29
either the pulp and paper or food and beverage sector (RTI 2018b). 30
The composition of waste disposed of in industrial waste landfills is expected to be more consistent in terms of 31
composition and quantity than that disposed of in MSW landfills. The amount of waste landfilled is assumed to be a 32
fraction of production that is held constant over the time series as explained in Annex 3.14. 33
Landfill CH4 recovery is not accounted for in industrial waste landfills. Data collected through EPA’s GHGRP for 34
industrial waste landfills (Subpart TT) show that only two of the 172 facilities, or 1 percent of facilities, have active 35
gas collection systems (EPA 2018b). However, because EPA’s GHGRP is not a national database and 36
comprehensive data regarding gas collection systems have not been published for industrial waste landfills, 37
assumptions regarding a percentage of landfill gas collection systems, or a total annual amount of landfill gas 38
collected for the non-reporting industrial waste landfills have not been made for the Inventory methodology. 39
The amount of CH4 oxidized by the landfill cover at industrial waste landfills was assumed to be 10 percent of the 40
CH4 generated (IPCC 2006; Mancinelli and McKay 1985; Czepiel et al. 1996) for all years. 41
Uncertainty and Time-Series Consistency 42
Several types of uncertainty are associated with the estimates of CH4 emissions from MSW and industrial waste 43
landfills when the FOD method is applied directly for 1990 to 2004 in the Waste Model and, to some extent, in the 44
GHGRP methodology. The approach used in the MSW emission estimates assumes that the CH4 generation 45
potential (Lo) and the rate of decay that produces CH4 from MSW, as determined from several studies of CH4 46
recovery at MSW landfills, are representative of conditions at U.S. MSW landfills. When this top-down approach is 47
7-12 DRAFT Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2017
applied at the nationwide level, the uncertainties are assumed to be less than when applying this approach to 1
individual landfills and then aggregating the results to the national level. In other words, the FOD method as applied 2
in this Inventory is not facility-specific modeling and while this approach may over- or under-estimate CH4 3
generation at some landfills if used at the facility-level, the result is expected to balance out because it is being 4
applied nationwide. 5
There is a high degree of uncertainty associated with the FOD model, particularly when a homogeneous waste 6
composition and hypothetical decomposition rates are applied to heterogeneous landfills (IPCC 2006). There is less 7
uncertainty in EPA’s GHGRP data because this methodology is facility-specific, uses directly measured CH4 8
recovery data (when applicable), and allows for a variety of landfill gas collection efficiencies, destruction 9
efficiencies, and/or oxidation factors to be used. 10
Uncertainty also exists in the scale-up factor applied for years 2005 to 2009 and in the back-casted emissions 11
estimates for 2005 to 2009. As detailed in RTI (2018a), limited information is available for landfills that do not 12
report to the GHGRP. RTI developed an initial list of landfills that do not report to the GHGRP with the intent of 13
quantifying the total waste-in-place for these landfills that would add up to the scale-up factor. Input was provided 14
by industry, LMOP, and additional EPA support. However, many gaps still exist and assumptions were made for 15
many landfills in order to estimate the scale-up factor. Additionally, a simple methodology was used to back-cast 16
emissions for 2005 to 2009 using the GHGRP emissions from 2010 to 2017. This methodology does not factor in 17
annual landfill to landfill changes in landfill CH4 generation and recovery. Because of this, an uncertainty factor of 18
25 percent is applied to emissions for 2005 to 2009. 19
With regard to the time series and as stated in 2006 IPCC Guidelines Volume 1: Chapter 5 Time-Series Consistency 20
(IPCC 2006), “the time series is a central component of the greenhouse gas inventory because it provides 21
information on historical emissions trends and tracks the effects of strategies to reduce emissions at the national 22
level. All emissions in a time series should be estimated consistently, which means that as far as possible, the time 23
series should be calculated using the same method and data sources in all years” (IPCC 2006). This chapter 24
however, recommends against back-casting emissions back to 1990 with a limited set of data and instead provides 25
guidance on techniques to splice, or join methodologies together. One of those techniques is referred to as the 26
overlap technique. The overlap technique is recommended when new data becomes available for multiple years. 27
This was the case with the GHGRP data for MSW landfills, where directly reported CH4 emissions data became 28
available for more than 1,200 MSW landfills beginning in 2010. The GHGRP emissions data had to be merged with 29
emissions from the FOD method to avoid a drastic change in emissions in 2010, when the datasets were combined. 30
EPA also had to consider that according to IPCC’s good practice, efforts should be made to reduce uncertainty in 31
Inventory calculations and that, when compared to the GHGRP data, the FOD method presents greater uncertainty. 32
In evaluating the best way to combine the two datasets, EPA considered either using the FOD method from 1990 to 33
2009, or using the FOD method for a portion of that time and back-casting the GHGRP emissions data to a year 34
where emissions from the two methodologies aligned. Plotting the back-casted GHGRP emissions against the 35
emissions estimates from the FOD method showed an alignment of the data in 2004 and later years which facilitated 36
the use of the overlap technique while also reducing uncertainty. Therefore, EPA decided to back-cast the GHGRP 37
emissions from 2009 to 2005 only, in order to merge the datasets and adhere to the IPCC Good Practice Guidance 38
for ensuring time series consistency. 39
Aside from the uncertainty in estimating landfill CH4 generation, uncertainty also exists in the estimates of the 40
landfill gas oxidized at MSW landfills. Facilities directly reporting to EPA’s GHGRP can use oxidation factors 41
ranging from 0 to 35 percent, depending on their facility-specific CH4 flux. As recommended by the 2006 IPCC 42
Guidelines for managed landfills, a 10 percent default oxidation factor is applied in the Inventory for both MSW 43
landfills (those not reporting to the GHGRP and for the years 1990 to 2004 when GHGRP data are not available) 44
and industrial waste landfills regardless of climate, the type of cover material, and/or presence of a gas collection 45
system. The number of published field studies measuring the rate of oxidation has increased substantially since the 46
2006 IPCC Guidelines were published and, as discussed in the Potential Improvements section, efforts will continue 47
to review the literature and revise this value, as appropriate. 48
Another significant source of uncertainty lies with the estimates of CH4 recovered by flaring and gas-to-energy 49
projects at MSW landfills that are sourced from the Inventory’s CH4 recovery databases (used for years 1990 to 50
2004). Four CH4 recovery databases are used to estimate nationwide CH4 recovery for MSW landfills for 1990 to 51
2004; whereas directly reported CH4 recovery is used for facilities reporting to the GHGRP for years 2005 to 2015. 52
The GHGRP MSW landfills database was added as a fourth recovery database starting with the 1990 through 2013 53
Waste 7-13
Inventory report. Relying on multiple databases for a complete picture introduces uncertainty because the coverage 1
and characteristics of each database differs, which increases the chance of double counting avoided emissions. 2
Additionally, the methodology and assumptions that go into each database differ. For example, the flare database 3
assumes the midpoint of each flare capacity at the time it is sold and installed at a landfill; the flare may be 4
achieving a higher capacity, in which case the flare database would underestimate the amount of CH4 recovered. 5
The LFGE database was updated annually until 2015. The flare database was populated annually until 2015 by the 6
voluntary sharing of flare sales data by select vendors, which likely underestimated recovery for landfills not 7
included in the three other recovery databases used by the Inventory. The EIA database has not been updated since 8
2006 and has, for the most part, been replaced by the GHGRP MSW landfills database. To avoid double counting 9
and to use the most relevant estimate of CH4 recovery for a given landfill, a hierarchical approach is used among the 10
four databases. GHGRP data and the EIA data are given precedence because facility data were directly reported; the 11
LFGE data are given second priority because CH4 recovery is estimated from facility-reported LFGE system 12
characteristics; and the flare data are given the lowest priority because this database contains minimal information 13
about the flare, no site-specific operating characteristics, and includes smaller landfills not included in the other 14
three databases (Bronstein et al. 2012). The coverage provided across the databases most likely represents the 15
complete universe of landfill CH4 gas recovery; however, the number of unique landfills between the four databases 16
does differ. 17
The 2006 IPCC Guidelines default value of 10 percent for uncertainty in recovery estimates was used for two of the 18
four recovery databases in the uncertainty analysis where metering of landfill gas was in place (for about 64 percent 19
of the CH4 estimated to be recovered). This 10 percent uncertainty factor applies to the LFGE database; 12 percent 20
to the EIA database; and 1 percent for the GHGRP MSW landfills dataset because of the supporting information 21
provided and rigorous verification process. For flaring without metered recovery data (the flare database), a much 22
higher uncertainty value of 50 percent is used. The compounding uncertainties associated with the four databases in 23
addition to the uncertainties associated with the FOD method and annual waste disposal quantities leads to the large 24
upper and lower bounds for MSW landfills presented in Table 7-5. 25
The lack of landfill-specific information regarding the number and type of industrial waste landfills in the United 26
States is a primary source of uncertainty with respect to the industrial waste generation and emission estimates. The 27
approach used here assumes that most of the organic waste disposed of in industrial waste landfills that would result 28
in CH4 emissions consists of waste from the pulp and paper and food processing sectors. However, because waste 29
generation and disposal data are not available in an existing data source for all U.S. industrial waste landfills, a 30
straight disposal factor is applied over the entire time series to the amount produced to determine the amounts 31
disposed. Industrial waste facilities reporting under EPA’s GHGRP do report detailed waste stream information, and 32
these data have been used to improve, for example, the DOC value used in the Inventory methodology for the pulp 33
and paper sector. A 10 percent oxidation factor is also applied to CH4 generation estimates for industrial waste 34
landfills, and carries the same amount of uncertainty as with the factor applied to CH4 generation for MSW landfills. 35
The results of the 2006 IPCC Guidelines Approach 2 quantitative uncertainty analysis are summarized in Table 7-5. 36
There is considerable uncertainty for the MSW landfills estimates due to the many data sources used, each with its 37
own uncertainty factor. 38
7-14 DRAFT Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2017
Table 7-5: Approach 2 Quantitative Uncertainty Estimates for CH4 Emissions from Landfills 1
(MMT CO2 Eq. and Percent) 2
Source Gas
2017 Emission
Estimate Uncertainty Range Relative to Emission Estimatea
(MMT CO2 Eq.) (MMT CO2 Eq.) (%)
Lower
Bound
Upper
Bound
Lower
Bound
Upper
Bound
Total Landfills CH4 107.7 95.7 151.2 -11% 40%
MSW CH4 92.8 69.4 116.5 -25% 26%
Industrial CH4 15.0 21.4 41.2 -43% 175%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
QA/QC and Verification 3
General quality assurance/quality control (QA/QC) procedures were applied consistent with the U.S. QA/QC plan, 4
which is in accordance with Vol. 1 Chapter 6 of 2006 IPCC Guidelines (see Annex 8 for more details). QA/QC 5
checks are performed for the transcription of the published data set (e.g., EPA’s GHGRP dataset) used to populate 6
the Inventory data set in terms of completeness and accuracy against the reference source. Additionally, all datasets 7
used for this category have been checked to ensure they are of appropriate quality and are representative of U.S. 8
conditions. The primary calculation spreadsheet is tailored from the 2006 IPCC Guidelines waste model and has 9
been verified previously using the original, peer-reviewed IPCC waste model. All model input values and 10
calculations were verified by secondary QA/QC review. Stakeholder engagements sessions in 2016 and 2017 were 11
used to gather input on methodological improvements and facilitate an external expert review on the methodology, 12
activity data, and emission factors. 13
Category-specific checks include the following: 14
• Evaluation of the secondary data sources used as inputs to the Inventory dataset to ensure they are 15
appropriately collected and are reliable; 16
• Cross-checking the data (activity data and emissions estimates) with previous years to ensure the data are 17
reasonable, and that any significant variation can be explained through the activity data; 18
• Conducting literature reviews to evaluate the appropriateness of country-specific emission factors (e.g., 19
DOC values, precipitation zones with respect to the application of the k values) given findings from recent 20
peer-reviewed studies; and 21
• Reviewing secondary datasets to ensure they are nationally complete and supplementing where necessary 22
(e.g., using a scale-up factor to account for emissions from landfills that do not report to EPA’s GHGRP). 23
A primary focus of the QA/QC checks in past Inventories was to ensure that CH4 recovery estimates were not 24
double-counted and that all LFGE projects and flares were included in the respective project databases. QA/QC 25
checks performed in the past for the recovery databases were not performed in this Inventory, because new data 26
were not added to the recovery databases in this Inventory year. For the GHGRP data, EPA verifies annual facility-27
level reports through a multi-step process (e.g., combination of electronic checks and manual reviews by staff) to 28
identify potential errors and ensure that data submitted to EPA are accurate, complete, and consistent. Based on the 29
results of the verification process, EPA follows up with facilities to resolve mistakes that may have occurred.5 30
Recalculations Discussion 31
Revisions to the individual facility reports submitted to EPA’s GHGRP can be made at any time and a portion of 32
facilities have revised their reports since 2010 for various reasons, resulting in changes to the total net CH4 33
emissions for MSW landfills. These recalculations increased net emissions for MSW landfills from 2005 to 2015 by 34
5 See <https://www.epa.gov/sites/production/files/2015-07/documents/ghgrp_verification_factsheet.pdf>.
Waste 7-15
less than 0.5 percent when compared to the previous Inventory report. Each Inventory year, the back-casted 1
emissions for 2005 to 2009 will be recalculated using the most recently verified data from the GHGRP. Changes in 2
these data result in changes to the back-casted emissions. 3
Planned Improvements 4
EPA has engaged in stakeholder outreach through a series of webinars between December 2016 and August 2017 to 5
increase the transparency in the Inventory methodology and to identify ideas and supplemental data sources that can 6
lead to methodological improvements. The areas where EPA is actively working on improvements include the 7
oxidation factor for 1990 to 2004, the default DOC value, the decay rate (k value), and the scale-up factor. 8
EPA investigated options to adjust the oxidation factor from the 10 percent currently used for 1990 to 2004 to 9
another value or approach such as the binned approach used in the GHGRP (e.g., 10 percent, 25 percent, or 35 10
percent based on methane flux). The oxidation factor currently applied in the later portion of the time series (2005 to 11
2016) averages at 19.5 percent due to the use of the GHGRP data while the earlier portion of the time series applies 12
the default of 10 percent. No changes to the oxidation factor have been made to the Inventory as a result of EPA’s 13
recent investigations. Efforts will continue to review new literature and revise the value, as appropriate. 14
The Inventory currently uses one value of 0.20 for the DOC for years 1990 to 2004. With respect to improvements 15
to the DOC value, EPA developed a database with MSW characterization data from individual studies across the 16
United States. EPA will review this data against the Inventory time series to assess the validity of the current DOC 17
value and how it is applied in the FOD method. Waste characterization studies vary greatly in terms of the 18
granularity of waste types included and the spatial boundaries of each study (e.g., one landfill, a metro area, 19
statewide). EPA also notes longer term recommendation from industry stakeholders regarding the DOC values used 20
in the GHGRP, in the context of new information on the composition of waste disposed in MSW landfills; these 21
newer values could then be reflected in the 2005 and later years of the Inventory. EPA is continuing to investigate 22
publicly available waste characterization studies and calculated DOC values resulting from the study data. 23
EPA began investigating the k values for the three climate types (dry, moderate, and wet) against new data and other 24
landfill gas models, and how they are applied to the percentage of the population assigned to these climate types. 25
EPA will also assess the uncertainty factor applied to these k values in the Waste Model. Like the DOC value, the k 26
values applied through the Waste Model are for the years 1990 to 2004; the k values for 2005 to 2017 are directly 27
incorporated into the net methane emissions reported to EPA’s GHGRP. EPA will continue investigating the 28
literature for available k value data to understand if the data warrant revisions to the k values used in the Waste 29
Model between 1990 to 2004. 30
With respect to the scale-up factor, EPA will periodically assess the impact to the waste-in-place and emissions data 31
from facilities that have resubmitted annual reports during any reporting years, are new reporting facilities, and from 32
facilities that have stopped reporting to the GHGRP to ensure national estimates are as complete as possible. 33
Facilities may stop reporting to the GHGRP when they meet the “off-ramp” provisions (reported less than 15,000 34
metric tons of CO2 equivalent for 3 consecutive years or less than 25,000 metric tons of CO2 equivalent for 5 35
consecutive years). If warranted, EPA will revise the scale-up factor to reflect newly acquired information to ensure 36
completeness of the Inventory. 37
EPA also conducted a brief investigation of the destruction efficiency applied for landfill gas flares and the 38
fluctuation in natural gas pricing and other potential factors that are impacting the development of new LFGTE 39
projects. EPA found that flare destruction efficiencies reported by several vendors ranged from 98 to 99.6 percent. 40
The EPA applies a 99 percent destruction efficiency for all landfill flares incorporated into the Inventory (from 1990 41
to 2004 because of the GHGRP data used in later years), which aligns well with the identified range. Therefore, no 42
revisions have been made to the flare destruction efficiency applied in the Inventory. 43
Box 7-3: Nationwide Municipal Solid Waste Data Sources 44
Municipal solid waste generated in the United States can be managed through landfilling, recycling, composting, 45
and combustion with energy recovery. There are three main sources for nationwide solid waste management data in 46
the United States: 47
• The BioCycle and Earth Engineering Center of Columbia University’s SOG in America surveys [no longer 48
published]; 49
7-16 DRAFT Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2017
• The EPA’s Advancing Sustainable Materials Management: Facts and Figures reports; and 1
• The EREF’s MSW Generation in the United States reports. 2
The SOG surveys and, now EREF, collected state-reported data on the amount of waste generated and the amount of 3
waste managed via different management options: landfilling, recycling, composting, and combustion. The survey 4
asked for actual tonnages instead of percentages in each waste category (e.g., residential, commercial, industrial, 5
construction and demolition, organics, tires) for each waste management option. If such a breakdown is not 6
available, the survey asked for total tons landfilled. The data are adjusted for imports and exports across state lines 7
so that the principles of mass balance are adhered to, whereby the amount of waste managed does not exceed the 8
amount of waste generated. The SOG and EREF reports present survey data aggregated to the state level. 9
The EPA Advancing Sustainable Materials Management: Facts and Figures reports use a materials flow 10
methodology, which relies heavily on a mass balance approach. Data are gathered from industry associations, key 11
businesses, similar industry sources, and government agencies (e.g., the Department of Commerce and the U.S. 12
Census Bureau) and are used to estimate tons of materials and products generated, recycled, combusted with energy 13
recovery or landfilled nationwide. The amount of MSW generated is estimated by estimating production and then 14
adjusting these values by addressing the imports and exports of produced materials to other countries. MSW that is 15
not recycled, composted, or combusted is assumed to be landfilled. The data presented in the report are nationwide 16
totals. 17
In this Inventory, emissions from solid waste management are presented separately by waste management option, 18
except for recycling of waste materials. Emissions from recycling are attributed to the stationary combustion of 19
fossil fuels that may be used to power on-site recycling machinery, and are presented in the stationary combustion 20
chapter in the Energy sector, although the emissions estimates are not called out separately. Emissions from solid 21
waste disposal in landfills and the composting of solid waste materials are presented in the Landfills and 22
Composting sections in the Waste sector of this report. In the United States, almost all incineration of MSW occurs 23
at waste-to-energy (WTE) facilities or industrial facilities where useful energy is recovered, and thus emissions from 24
waste incineration are accounted for in the Incineration chapter of the Energy sector of this report. 25
26
Box 7-4: Overview of the Waste Sector 27
As shown in Figure 7-2 and Figure 7-3, landfilling of MSW is currently and has been the most common waste 28
management practice. A large portion of materials in the waste stream are recovered for recycling and composting, 29
which is becoming an increasingly prevalent trend throughout the country. Materials that are composted and 30
recycled would have previously been disposed in a landfill. 31
Figure 7-2: Management of Municipal Solid Waste in the United States, 2015 32
33
Source: EPA (2018c) Note: 2015 is the latest year of available data. 34
Waste 7-17
Figure 7-3: MSW Management Trends from 1990 to 2015 1
2
Source: EPA (2018c). Note: 2015 is the latest year of available data. 3
Table 7-6 presents a typical composition of waste disposed of at a typical MSW landfill in the United States over 4
time. It is important to note that the actual composition of waste entering each landfill will vary from that presented 5
in Table 7-6. Understanding how the waste composition changes over time, specifically for the degradable waste 6
types (i.e., those types known to generate CH4 as they break down in a modern MSW landfill), is important for 7
estimating greenhouse gas emissions. Increased diversion of degradable materials so that they are not disposed of in 8
landfills reduces the CH4 generation potential and CH4 emissions from landfills. For certain degradable waste types 9
(i.e., paper and paperboard), the amounts discarded have decreased over time due to an increase in waste diversion 10
through recycling and composting (see Table 7-6 and Figure 7-4). As shown in Figure 7-4, the diversion of food 11
scraps has been consistently low since 1990 because most cities and counties do not practice curbside collection of 12
these materials. Neither Table 7-6 nor Figure 7-4 reflect the frequency of backyard composting of yard trimmings 13
and food waste because this information is largely not collected nationwide and is hard to estimate. 14
Table 7-6: Materials Discardeda in the Municipal Waste Stream by Waste Type from 1990 to 15
2015 (Percent)b 16
Waste Type 1990 2005 2010 2011c 2012 2013 2014 2015
Paper and Paperboard 30.0% 24.7% 16.1% 14.7% 14.7% 15.0% 14.3% 13.3%
7-18 DRAFT Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2017
a Discards after materials and compost recovery. In this table, discards include combustion with energy recovery. Does not
include construction & demolition debris, industrial process wastes, or certain other wastes. b Data for all years except 2011 are from the EPA’s Advancing Sustainable Materials Management: Facts and Figures 2015
Tables and Figures report (Table 4) published in July 2018 (EPA 2018c). c 2011 data are not included in the most recent Advancing Sustainable Materials Management: Facts and Figures report (2014),
thus data from the 2013 report (Table 3) was kept in place for 2011 (EPA 2015b). d Includes electrolytes in batteries and fluff pulp, feces, and urine in disposable diapers. Details may not add to totals due to
rounding.
Note: 2015 is the latest year of available data.
Figure 7-4: Percent of Degradable Materials Diverted from Landfills from 1990 to 2015 1
(Percent) 2
3
Source: (EPA 2018c). Note: 2015 is the latest year of available data. 4
5
Box 7-5: Description of a Modern, Managed Landfill 6
Modern, managed landfills are well-engineered facilities that are located, designed, operated, and monitored to 7
ensure compliance with federal, state, and tribal regulations. Municipal solid waste (MSW) landfills must be 8
designed to protect the environment from contaminants which may be present in the solid waste stream. 9
Additionally, many new landfills collect and destroy landfill gas through flares or landfill gas-to-energy projects. 10
Requirements for affected MSW landfills may include: 11
• Siting requirements to protect sensitive areas (e.g., airports, floodplains, wetlands, fault areas, seismic 12
impact zones, and unstable areas); 13
• Design requirements for new landfills to ensure that Maximum Contaminant Levels (MCLs) will not be 14
exceeded in the uppermost aquifer (e.g., composite liners and leachate collection systems); 15
• Leachate collection and removal systems; 16
• Operating practices (e.g., daily and intermediate cover, receipt of regulated hazardous wastes, use of 17
landfill cover material, access options to prevent illegal dumping, use of a collection system to prevent 18
stormwater run-on/run-off, record-keeping); 19
• Air monitoring requirements (explosive gases); 20
• Groundwater monitoring requirements; 21
• Closure and post-closure care requirements (e.g., final cover construction); and 22
Waste 7-19
• Corrective action provisions. 1
Specific federal regulations that affected MSW landfills must comply with include the 40 CFR Part 258 (Subtitle D 2
of RCRA), or equivalent state regulations and the NSPS 40 CFR Part 60 Subpart WWW. Additionally, state and 3
tribal requirements may exist.6 4
5
7.2 Wastewater Treatment (CRF Source 6
Category 5D) 7
Wastewater treatment processes can produce anthropogenic methane (CH4) and nitrous oxide (N2O) emissions. 8
Wastewater from domestic and industrial sources is treated to remove soluble organic matter, suspended solids, 9
pathogenic organisms, and chemical contaminants.7 Treatment may either occur on site, most commonly through 10
septic systems or package plants, or off site at centralized treatment systems. In the United States, approximately 19 11
percent of domestic wastewater is treated in septic systems or other on-site systems, while the rest is collected and 12
treated centrally (U.S. Census Bureau 2015). Centralized wastewater treatment systems may include a variety of 13
processes, ranging from lagooning to advanced tertiary treatment technology for removing nutrients. Some 14
wastewater may also be treated through the use of constructed (or semi-natural) wetland systems, though it is much 15
less common in the United States (ERG 2016). Constructed wetlands may be used as the primary method of 16
wastewater treatment, or as a tertiary treatment step following settling and biological treatment. Constructed 17
wetlands develop natural processes that involve vegetation, soil, and associated microbial assemblages to trap and 18
treat incoming contaminants (IPCC 2014). 19
Soluble organic matter is generally removed using biological processes in which microorganisms consume the 20
organic matter for maintenance and growth. The resulting biomass (sludge) is removed from the effluent prior to 21
discharge to the receiving stream. Microorganisms can biodegrade soluble organic material in wastewater under 22
aerobic or anaerobic conditions, where the latter condition produces CH4. During collection and treatment, 23
wastewater may be accidentally or deliberately managed under anaerobic conditions. In addition, the sludge may be 24
further biodegraded under aerobic or anaerobic conditions. The generation of N2O may also result from the 25
treatment of domestic wastewater during both nitrification and denitrification of the nitrogen (N) present, usually in 26
the form of urea, ammonia, and proteins. These compounds are converted to nitrate (NO3) through the aerobic 27
process of nitrification. Denitrification occurs under anoxic conditions (without free oxygen) and involves the 28
biological conversion of nitrate into dinitrogen gas (N2). Nitrous oxide can be an intermediate product of both 29
processes but has typically been associated with denitrification. Recent research suggests that higher emissions of 30
N2O may in fact originate from nitrification (Ahn et al. 2010). Other more recent research suggests that N2O may 31
also result from other types of wastewater treatment operations (Chandran 2012). 32
The principal factor in determining the CH4 generation potential of wastewater is the amount of degradable organic 33
material in the wastewater. Common parameters used to measure the organic component of the wastewater are the 34
biochemical oxygen demand (BOD) and chemical oxygen demand (COD). Under the same conditions, wastewater 35
with higher COD (or BOD) concentrations will generally yield more CH4 than wastewater with lower COD (or 36
BOD) concentrations. BOD represents the amount of oxygen that would be required to completely consume the 37
organic matter contained in the wastewater through aerobic decomposition processes, while COD measures the total 38
material available for chemical oxidation (both biodegradable and non-biodegradable). The BOD value is most 39
commonly expressed in milligrams of oxygen consumed per liter of sample during 5 days of incubation at 20°C, or 40
BOD5. Because BOD is an aerobic parameter, it is preferable to use COD to estimate CH4 production, since CH4 is 41
6 For more information regarding federal MSW landfill regulations, see
<http://www.epa.gov/osw/nonhaz/municipal/landfill/msw_regs.htm>. 7 Throughout the Inventory, emissions from domestic wastewater also include any commercial and industrial wastewater
collected and co-treated with domestic wastewater.
7-20 DRAFT Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2017
produced only in anaerobic conditions. The principal factor in determining the N2O generation potential of 1
wastewater is the amount of N in the wastewater. The variability of N in the influent to the treatment system, as well 2
as the operating conditions of the treatment system itself, also impact the N2O generation potential. 3
In 2017, CH4 emissions from domestic wastewater treatment were 8.6 MMT CO2 Eq. (342 kt CH4). Emissions 4
remained fairly steady from 1990 through 1999 but have decreased since that time due to decreasing percentages of 5
wastewater being treated in anaerobic systems, generally including reduced use of on-site septic systems and central 6
anaerobic treatment systems (EPA 1992, 1996, 2000, and 2004; U.S. Census Bureau 2015). In 2017, CH4 emissions 7
from industrial wastewater treatment were estimated to be 5.7 MMT CO2 Eq. (229 kt CH4) and include the newly 8
added sector of breweries. Industrial emission sources have generally increased across the time series through 1999 9
and then fluctuated up and down with production changes associated with the treatment of wastewater from the pulp 10
and paper manufacturing, meat and poultry processing, fruit and vegetable processing, starch-based ethanol 11
production, petroleum refining, and brewery industries. Table 7-7 and Table 7-8 provide CH4 emission estimates 12
from domestic and industrial wastewater treatment. 13
With respect to N2O, the United States identifies two distinct sources for N2O emissions from domestic wastewater: 14
emissions from centralized wastewater treatment processes, and emissions from effluent from centralized treatment 15
systems that has been discharged into aquatic environments. The 2017 emissions of N2O from centralized 16
wastewater treatment processes and from effluent were estimated to be 0.4 MMT CO2 Eq. (1.2 kt N2O) and 4.6 17
MMT CO2 Eq. (15.4 kt N2O), respectively. Total N2O emissions from domestic wastewater were estimated to be 5.0 18
MMT CO2 Eq. (16.6 kt N2O). Nitrous oxide emissions from wastewater treatment processes gradually increased 19
across the time series as a result of increasing U.S. population and protein consumption. Nitrous oxide emissions are 20
not estimated from industrial wastewater treatment because there is no IPCC methodology provided or industrial 21
wastewater emission factors available. Table 7-7 and Table 7-8 provide N2O emission estimates from domestic 22
wastewater treatment. 23
Table 7-7: CH4 and N2O Emissions from Domestic and Industrial Wastewater Treatment 24
(MMT CO2 Eq.) 25
Activity 1990 2005 2013 2014 2015 2016 2017
CH4 15.3 15.5 14.4 14.4 14.6 14.3 14.3
Domestic 10.4 10.0 8.9 9.0 9.1 8.7 8.6
Industriala 4.9 5.4 5.5 5.4 5.5 5.6 5.7
N2O 3.4 4.4 4.7 4.8 4.8 4.9 5.0
Centralized WWTP 0.2 0.3 0.3 0.3 0.3 0.4 0.4
Domestic Effluent 3.2 4.1 4.3 4.4 4.4 4.5 4.6
Total 18.7 19.8 19.0 19.1 19.3 19.1 19.2 a Industrial activity includes the pulp and paper manufacturing, meat and poultry processing, fruit
and vegetable processing, starch-based ethanol production, petroleum refining, and breweries
industries.
Note: Totals may not sum due to independent rounding.
Table 7-8: CH4 and N2O Emissions from Domestic and Industrial Wastewater Treatment (kt) 26
Activity 1990 2005 2013 2014 2015 2016 2017
CH4 612 618 574 575 582 571 571
Domestic 418 401 355 359 363 347 342
Industriala 194 217 219 216 219 224 229
N2O 11 15 16 16 16 16 17
Centralized WWTP 1 1 1 1 1 1 1
Domestic Effluent 11 14 15 15 15 15 15 a Industrial activity includes pulp and paper manufacturing, meat and poultry processing, fruit and
vegetable processing, starch-based ethanol production, petroleum refining, and breweries.
Note: Totals may not sum due to independent rounding.
Waste 7-21
Methodology 1
Domestic Wastewater CH4 Emission Estimates 2
Domestic wastewater CH4 emissions originate from both septic systems and from centralized treatment systems, 3
such as publicly owned treatment works (POTWs). Within these centralized systems, CH4 emissions can arise from 4
aerobic systems that are not well managed or that are designed to have periods of anaerobic activity (e.g., 5
constructed wetlands and facultative lagoons), anaerobic systems (anaerobic lagoons and anaerobic reactors), and 6
from anaerobic digesters when the captured biogas is not completely combusted. The methodological equations are: 7
Production = Gallons ethanol produced (wet milling or dry milling) 15
Flow = Gallons wastewater generated per gallon ethanol produced 16
COD = COD concentration in influent (g/l) 17
3.785 = Conversion factor, gallons to liters 18
%Plantso = Percent of plants with onsite treatment 19
%WWa,p = Percent of wastewater treated anaerobically in primary treatment 20
%CODp = Percent of COD entering primary treatment 21
%Plantsa = Percent of plants with anaerobic secondary treatment 22
%Plantst = Percent of plants with other secondary treatment 23
%WWa,s = Percent of wastewater treated anaerobically in anaerobic secondary treatment 24
%WWa,t = Percent of wastewater treated anaerobically in other secondary treatment 25
%CODs = Percent of COD entering secondary treatment 26
Bo = Maximum methane producing capacity (g CH4/g COD) 27
MCF = Methane correction factor 28
% Recovered = Percent of wastewater treated in system with emission recovery 29
% Not Recovered = 1 - percent of wastewater treated in system with emission recovery 30
DE = Destruction efficiency of recovery system 31
1/109 = Conversion factor, g to kt 32
A time series of CH4 emissions for 1990 through 2017 was developed based on production data from the Renewable 33
Fuels Association (Cooper 2018). 34
Petroleum Refining. Petroleum refining wastewater treatment operations have the potential to produce CH4 35
emissions from anaerobic wastewater treatment. EPA’s Office of Air and Radiation performed an Information 36
Collection Request (ICR) for petroleum refineries in 2011.8 Of the responding facilities, 23.6 percent reported using 37
non-aerated surface impoundments or other biological treatment units, both of which have the potential to lead to 38
anaerobic conditions (ERG 2013b). In addition, the wastewater generation rate was determined to be 26.4 gallons 39
per barrel of finished product (ERG 2013b). An average COD value in the wastewater was estimated at 0.45 kg/m3 40
(Benyahia et al. 2006). A default MCF of 0.3 was used for partially aerobic systems. 41
The equation used to calculate CH4 generation at petroleum refining wastewater treatment systems is presented 42
below: 43
Methane = Flow × COD × %TA × Bo × MCF 44
where, 45
Flow = Annual flow treated through anaerobic treatment system (m3/year) 46
COD = COD loading in wastewater entering anaerobic treatment system (kg/m3) 47
8 Available online at <https://www.epa.gov/stationary-sources-air-pollution/comprehensive-data-collected-petroleum-refining-
sector>
Waste 7-29
%TA = Percent of wastewater treated anaerobically on site 1
Bo = Maximum methane producing potential of industrial wastewater (kg CH4/kg COD) 2
MCF = Methane correction factor 3
A time series of CH4 emissions for 1990 through 2017 was developed based on production data from the EIA 2018. 4
Breweries. Since 2010, the number of breweries has increased from less than 2,000 to greater than 6,000 (Brewers 5
Association 2018). This increase has primarily been driven by craft breweries, which have increased by over 250 6
percent during that period. Craft breweries were defined as breweries producing less than six million barrels of beer 7
per year, and non-craft breweries produce greater than six million barrels. With their large amount of water use and 8
high strength wastewater, breweries generate considerable CH4 emissions from anaerobic wastewater treatment. 9
However, because many breweries recover their CH4, their emissions are much lower. 10
The Alcohol and Tobacco Tax and Trade Bureau (TTB) provides total beer production in barrels per year for 11
different facility size categories from 2007 to the present (TTB 2018). For years prior to 2007 where TTB data were 12
not readily available, the Brewers Almanac (Beer Institute 2011) was used, along with an estimated percent of craft 13
and non-craft breweries based on the breakdown of craft and non-craft for the years 2007 through 2017. 14
The amount of water usage by craft breweries was estimated using the Brewers Association’s 2015 Sustainability 15
Benchmarking Report (Brewers Association 2016a) and the 2016 Benchmarking Update (Brewers Association 16
2017; ERG 2018b). Non-craft brewery water usage values were from the Beverage Industry Environmental 17
Roundtable (BIER) benchmarking study (BIER 2017). 18
To determine the overall amount of wastewater produced, data on water use per unit of production and a 19
wastewater-to-water ratio were used from the Benchmarking Report (Brewers Association 2016a) for both craft and 20
non-craft breweries. Since brewing is a batch process, and different operations have varying organic loads, full-21
strength brewery wastewater can vary widely on a day to day basis. However, the organic content of brewery 22
wastewater does not substantially change between craft and non-craft breweries. On average, full-strength 23
wastewater is about 10,600 mg/L BOD, with a typical BOD:COD ratio of 0.6 (Brewers Association 2016b). Some 24
breweries may collect and discharge high-strength wastewater from particular brewing processes (known as “side 25
streaming”) to a POTW, greatly reducing the organics content of the wastewater that is treated on site. 26
Subsequently, the MCF for discharge to a POTW was assumed to be zero (ERG 2018b). 27
Breweries may treat some or all of their wastewater on site prior to discharge to a POTW or receiving water. On-site 28
treatment operations can include physical treatment (e.g., screening, settling) which are not expected to contribute to 29
CH4 emissions, or biological treatment, which may include aerobic treatment or pretreatment in anaerobic reactors 30
(ERG 2018b). The IPCC default Bo of 0.25 kg CH4/kg COD and default MCFs of 0.8 for anaerobic treatment and 0 31
for aerobic treatment were used to estimate the CH4 produced from these on-site treatment systems (IPCC 2006). 32
The amount of CH4 recovered through anaerobic wastewater treatment was estimated, and a 99 percent destruction 33
efficiency was used (ERG 2018b; Stier J. 2018). Very limited activity data are available on the number of U.S. 34
breweries that are performing side streaming or pretreatment of wastewater prior to discharge. 35
The assumed distribution of wastewater treatment for craft and non-craft breweries are shown in Table 7-15. 36
Table 7-15: Wastewater Treatment Distribution for Breweries 37
Treatment Type
Operation Type Non-Craft Craft
Discharge to POTW with no pretreatment 0% 99% Discharge to POTW following side streaming 0% 0.5% Pretreatment with aerobic biological treatment 1% 0% Pretreatment with anaerobic reactor 99% 0.5%
Source: Stier, J. (2018)
Methane emissions were then estimated for non-craft breweries and for craft breweries as follows: 38